Geodesic
Solution of the fracture detection problem by machine learning methods
Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ, Tome 491 (2020), pp. 107-110.

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Inverse problems of fracture exploration seismology are solved using machine learning methods. A single fracture of fixed size and subvertical orientation is considered in the two-dimensional case. The spatial position and the inclination angle of the fracture are determined using a neural network. The training set consists of solutions of direct problems produced by the grid-characteristic method on regular rectangular meshes in the form of synthetic seismograms obtained by measuring the vertical velocity on the surface of the medium.
Keywords: mathematical modeling, grid-characteristic method, machine learning, neural networks, inverse exploration seismology problem, fracture. 
@article{DANMA_2020_491_a21,
     author = {M. V. Muratov and V. A. Biryukov and I. B. Petrov},
     title = {Solution of the fracture detection problem by machine learning methods},
     journal = {Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleni\^a},
     pages = {107--110},
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     volume = {491},
     year = {2020},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/DANMA_2020_491_a21/}
}
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M. V. Muratov; V. A. Biryukov; I. B. Petrov. Solution of the fracture detection problem by machine learning methods. Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ, Tome 491 (2020), pp. 107-110. http://geodesic.mathdoc.fr/item/DANMA_2020_491_a21/

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